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Record W1514170222

Development of a 3d finite element model of the human external ear for simulation of the auditory occlusion effect

2011· article· en· W1514170222 on OpenAlexafffund
Martin Brummund, Yvan Petit, Franck Sgard, Frédéric Laville

Bibliographic record

VenueEspace ÉTS (ETS) · 2011
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsÉcole de Technologie Supérieure
FundersInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsFinite element methodAcousticsEar canalAuditory canalHuman earEngineeringComputer scienceStructural engineeringPhysicsAnatomyMedicine
DOInot available

Abstract

fetched live from OpenAlex

Numerical models present a valuable means to improve the outlined shortcomings because they can aid to better assess and design hearing protectors. The present study describes the development of a novel coupled linear elasto-acoustic 3D finite element model of the human external ear. This genuine model is employed to simulate the auditory OE. The biomaterial properties of the bony and cartilaginous tissues were approximated using literature findings. The skin tissue of the ear canal entrance and walls was modeled using soft rubber. The obtained results indicate that the implemented 3D finite element model can be employed to calculate the auditory OE. Obtained OEs vary as a function of insertion depth and are plausible when compared to literature findings. Comprehensive tests regarding the influence of each of these factors have yet to be completed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.277
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2011
Admission routes2
Has abstractyes

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